Artificial Intelligence-Guided De Novo Molecular Design Targeting COVID-19.

ABSTRACT: An extensive search for active therapeutic agents against the SARS-CoV-2 is being conducted across the globe. While computational docking simulations remain a popular method of choice for the in silico ligand design and high-throughput screening of therapeutic agents, it is severely limited in the discovery of new candidate ligands owing to the high computational cost and vast chemical space. Here, we present a de novo molecular design strategy that leverages artificial intelligence (AI) to discover new therapeutic agents against SARS-CoV-2. A Monte Carlo tree search algorithm combined with a multitask neural network surrogate model for expensive docking simulations, and recurrent neural networks for rollouts, is used in an iterative search and retrain strategy. Using Vina sc

SUBMITTER: Srinivasan S 

PROVIDER: S-EPMC8154149 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature